• Title/Summary/Keyword: 과학성

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Predictors of Continuity of Care after Inpatient Discharge of Patients with Bipolar Disorder : A Retrospective Chart Review Study in a University Hospital (양극성 장애 환자에서 퇴원 이후 외래 치료 유지에 영향을 미치는 예측인자 : 일 대학병원 후향적 의무기록 조사연구)

  • Wang, Hee Ryung;Jung, Young-Eun;Song, Hoo Rim;Jun, Tae-Youn;Kim, Kwang-Su;Bahk, Won-Myong
    • Mood & Emotion
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    • v.9 no.2
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    • pp.126-132
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    • 2011
  • Background and Objectives : This study aims to identify sociodemographic and disease-related variables which predicts continuity of outpatient treatment after discharge among bipolar patients. Materials and Method : The medical records of patients who discharged with the diagnosis of bipolar disorder from Department of Psychiatry, St. Mary's hospital from 2005 to 2009 were reviewed. Data on sociodemographic and disease-related variables were analyzed. Results : It showed older age, higher rate of male and higher rate of being married in 1-year follow-up group than in non-follow-up group. And it showed longer duration of index hospitalization, higher rate of previous psychiatric outpatient treatment within 3 months before index hospitalization, higher rate of involuntary admission in 1-year follow-up group than in non-follow-up group. The univariate logistic regression analysis revealed that older age, being male, previous psychiatric treatment and longer duration of index hospitalization were significantly related to an increased likelihood of 1-year follow-up visits. Conclusion : Age, sex, history of previous psychiatric treatment, and duration of hospitalization seems to have influence on continuity of outpatient treatment after discharge.

Development and Validation of Distributed Cognition Theory Based Instructional Strategy in Science Class Using Technology (테크놀로지 활용 과학 수업에서 분산인지 이론 기반 수업 전략의 개발 및 타당화)

  • Ja-Heon Noh;Jun-Ho Son;Jong-Hee Kim
    • Journal of the Korean Society of Earth Science Education
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    • v.17 no.1
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    • pp.1-19
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    • 2024
  • This study is a design and development study that developed instructional strategies based on distributed cognitive theory for science classes using technology according to procedures that ensured reliability and validity. To develop instructional strategies, development study and validation study were conducted according to design and development research methodology procedures. In the development study, an initial instructional strategy was developed through prior literature review and prior expert review. In the validation study, the instructional strategy was validated using internal validation (expert validation, usability evaluation) and external validation (field application evaluation) methods, and the final instructional strategy was developed. The final instructional strategy consisted of 3 instructional principles, 9 instructional strategies, and 38 detailed guidelines. Through this study, the researcher suggested the suitability of instructional strategies for science classes using technology, the usefulness of blocks and teaching and learning processes, the possibility of using technology as a cognitive tool, the need for teachers' efforts to cultivate teaching capabilities using technology, and the needs lesson plan that takes into account conditions affecting the application of instructional strategies.

Integration of AI, Causality, and Social Sciences: Understanding Social Phenomena through Causal Deep Learning (AI, 인과성, 사회과학의 통합: 인과 딥러닝을 통한 사회현상의 이해)

  • Seog-Min Lee
    • Analyses & Alternatives
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    • v.8 no.3
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    • pp.125-150
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    • 2024
  • This paper explores the integration of artificial intelligence and causal inference in social science research, focusing on causal deep learning. We examine key theories including Pearl's Structural Causal Model, Rubin's Potential Outcomes Framework, and Schölkopf's Causal Representation Learning. Methodologies such as structural causal models with deep learning, counterfactual reasoning, and causal discovery algorithms are discussed. The paper presents applications in social media analysis, economic policy, public health, and education, demonstrating how causal deep learning enables nuanced understanding of complex social phenomena. Key challenges addressed include model complexity, causal identification, interpretability, and ethical considerations like fairness and privacy. Future research directions include developing new AI architectures, real-time causal inference, and multi-domain generalization. While limitations exist, causal deep learning shows significant potential for enhancing social science research and informing evidence-based policy-making, contributing to addressing complex social challenges globally.

Clinical Significance of Antibodies Against Platelet HLA Class I in Children with Idiopathic Thrombocytopenic Purpura (소아 특발성 혈소판 감소증에서 항-HLA Class I항체의 임상적 의미)

  • Lee, Hong Jun;Yeom, Jung-Sook;Park, Ji Sook;Park, Eun Sil;Seo, Ji-Hyun;Lim, Jae Young;Park, Chan-Hoo;Woo, Hyang-Ok;Youn, Hee-Shang
    • The Korean Journal of Blood Transfusion
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    • v.24 no.3
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    • pp.233-240
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    • 2013
  • Background: A previous history of transfusion has been known to be associated with production of anti-HLA class I antibodies. However, platelet glycoproteins are the main target of idiopathic thrombocytopenic purpura (ITP). The mechanism of antibody production is known to differ significantly between glycoproteins and anti-HLA class I. The aim of this study was to evaluate the clinical significance of anti-HLA class I antibodies in childhood ITP. Methods: Enrollment for the normal control group targeted 48 people who visited Gyeongsang National University Hospital from 1990 to 2010, and 48 young children with ITP. Anti-glycoproteins and anti-HLA class I antibodies were tested using the Modified Antigen Capture Enzyme-linked immunosorbent assay (MACE) kit. Results: The positive rate of anti-HLA antibodies was significantly different [36/39 (92.3%) vs 29/46 (63%)] [ITP group vs normal control group] (P=0.002). The mean positive S/C ratio of anti-HLA antibodies was also significantly different (3.55 vs 1.51) [ITP group vs normal control group] (P=0.0000). The positive rate of anti-HLA did not differ significantly between the transfused group and the non-transfused group [12/12 (100%) vs 24/27 (88%)] [transfused ITP vs non-transfused ITP]. The mean positive S/C ratio of anti-HLA antibodies did not differ significantly between the transfused ITP group and the non-transfused ITP group (4.30 vs 3.25) [transfused ITP vs non-transfused ITP]. Consecutive testing showed that positive rate and positive S/C ratio of anti-HLA antibodies did not change significantly between sampling times in both groups [transfused ITP vs non-transfused ITP] (P=1.00 and P=0.15). Conclusion: Anti-HLA class I antibodies may be involved in childhood ITP. Transfusion did not affect the course of childhood ITP.